Accurate Depth-map estimation for 3D face modeling (original) (raw)

Fast and High Resolution 3D Face Scanning

2007 IEEE International Conference on Image Processing, 2007

In this work, we present a framework to capture 3D models of faces in high resolutions with low computational load. The system captures only two pictures of the face, one illuminated with a colored stripe pattern and one with regular white light. The former is needed for the depth calculation, the latter is used as texture. Having these two images a combination of specialized algorithms is applied to generate a 3D model. The results are shown in different views: simple surface, wire grid respective polygon mesh or textured 3D surface.

3D Face Reconstruction from 2D Images

2008 Digital Image Computing: Techniques and Applications, 2008

This paper surveys the topic of 3D face reconstruction using 2D images from a computer science perspective. Various approaches have been proposed as solutions for this problem but most have their limitations and drawbacks. Shape from shading, Shape from silhouettes, Shape from motion and Analysis by synthesis using morphable models are currently regarded as the main methods of attaining the facial information for reconstruction of its 3D counterpart. Though this topic has gained a lot of importance and popularity, a fully accurate facial reconstruction mechanism has not yet being identified due to the complexity and ambiguity involved. This paper discusses about the general approaches of 3D face reconstruction and their drawbacks. It concludes with an analysis of several implementations and some speculations about the future of 3D face reconstruction.

From 2D images to 3D face geometry

Proceedings of the Second International Conference on Automatic Face and Gesture Recognition, 1996

This paper presents a global scheme for 3D face reconstruction and face segmentation into a limited number of analytical patches from stereo images. From a depth map, we generate a 3D model of the face which is iteratively deformed under stereo and shape-from-shading constraints as well as differential features. This model enables us to improve the quality of the depth map, from which we perform the segmentation and the approximation of the surface.

IMAGE BASED 3D FACE RECONSTRUCTION: A SURVEY

International Journal of Image and Graphics, 2009

The use of 3D data in face image processing applications has received considerable attention during the last few years. A major issue for the implementation of 3D face processing systems is the accurate and real time acquisition of 3D faces using low cost equipment. In this paper we provide a survey of 3D reconstruction methods used for generating the 3D appearance of a face using either a single or multiple 2D images captured with ordinary equipment such as digital cameras and camcorders. In this context we discuss various issues pertaining to the general problem of 3D face reconstruction such as the existence of suitable 3D face databases, correspondence of 3D faces, feature detection, deformable 3D models and typical assumptions used during the reconstruction process. Different approaches to the problem of 3D reconstruction are presented and for each category the most important advantages and disadvantages are outlined. In particular we describe example-based methods, stereo methods, video-based methods and silhouette-based methods. The issue of performance evaluation of 3D face reconstruction algorithms, the state of the art and future trends are also discussed.

An Evaluation of Three Popular Computer Vision Approaches for 3-D Face Synthesis

Lecture Notes in Computer Science, 2006

We have evaluated three computer approaches to 3-D reconstruction-passive computational binocular stereo and active structured lighting and photometric stereo-in regard to human face reconstruction for modelling virtual humans. An integrated experimental environment simultaneously acquired images for 3-D reconstruction and data from a 3-D scanner which provided an accurate ground truth. Our goal was to determine whether today's computer vision approaches are accurate and fast enough for practical 3-D facial reconstruction applications. We showed that the combination of structured lighting with symmetric dynamic programming stereo has good prospects with reasonable processing time and accuracy.

Chapter 2 A SURVEY ON 3D MODELING OF HUMAN FACES FOR FACE RECOGNITION

In its quest for more reliability and higher recognition rates the face recognition community has been focusing more and more on 3D based recognition. Depth information adds another dimension to facial features and provides ways to minimize the effects of pose and illumination variations for achieving greater recognition accuracy. This chapter reviews, therefore, the major techniques for 3D face modeling, the first step in any 3D assisted face recognition system. The reviewed techniques are laser range scans, 3D from structured light projection, stereo vision, morphing, shape from motion, shape from space carving, and shape from shading. Concepts, accuracy, feasibility, and limitations of these techniques and their effectiveness for 3D face recognition are discussed.

Automatic 3D Reconstruction for Face Recognition

2004

An analysis-by-synthesis framework for face recognition with variant pose, illumination and expression (PIE) is proposed in this paper. First, an efficient 2D-to-3D integrated face reconstruction approach is introduced to reconstruct a personalized 3D face model from a single frontal face image with neutral expression and normal illumination; Then, realistic virtual faces with different PIE are synthesized based on the personalized 3D face to characterize the face subspace; Finally, face recognition is conducted based on these representative virtual faces. Compared with other related works, this framework has the following advantages: 1) only one single frontal face is required for face recognition, which avoids the burdensome enrollment work; 2) the synthesized face samples provide the capability to conduct recognition under difficult conditions like complex PIE; and 3) the proposed 2D-to-3D integrated face reconstruction approach is fully automatic and more efficient. The extensive experimental results show that the synthesized virtual faces significantly improve the accuracy of face recognition with variant PIE.

Real-Time Face Reconstruction from a Single Depth Image

2014 2nd International Conference on 3D Vision, 2014

Figure 1: Our method starts with estimating dense correspondences on an input depth image, using a discriminative model. A generative model parametrized by blend shapes is then utilized to further refine these correspondences. The final correspondence field is used for per-frame 3D face shape and expression reconstruction, allowing for texture unwrapping, retexturing or retargeting in real-time.

Accurate 2D Facial Depth Models Derived from a 3D Synthetic Dataset

2021 IEEE International Conference on Consumer Electronics (ICCE), 2021

As Consumer Technologies (CT) seeks to engage and interact more closely with the end-user it becomes important to observe and analyze a user's interaction with CT devices and associated services. One of the most useful modes for monitoring a user is to analyze a real-time video stream of their face. Facial expressions, movements and biometrics all provide important information, but obtaining a calibrated input with 3D accuracy from a single camera requires accurate knowledge of the facial depth and distance of different features from the camera. In this paper, a method is proposed to generate synthetic highaccuracy human facial depth from synthetic 3D face models. The generated synthetic human facial dataset is then used in Convolutional Neural Networks (CNN's) for monocular depth facial estimation and the results of the experiments are presented.